Differential MRI analysis for quantification of low grade glioma growth

被引:14
作者
Angelini, Elsa D. [1 ]
Delon, Julie
Bah, Alpha Boubacar [2 ]
Capelle, Laurent [2 ]
Mandonnet, Emmanuel [3 ]
机构
[1] Telecom ParisTech, Dept Signal & Image Proc, Inst Telecom, CNRS LTCI, F-75013 Paris, France
[2] Hop La Pitie Salpetriere, Dept Neurosurg, F-75013 Paris, France
[3] Hop Lariboisiere, Dept Neurosurg, F-75010 Paris, France
关键词
MRI; Brain tumor; Longitudinal studies; Low-grade glioma; TUMOR SEGMENTATION; IMAGES; DIFFUSION; TIME; REGISTRATION; ALGORITHMS; DYNAMICS; MODEL;
D O I
10.1016/j.media.2011.05.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A differential analysis framework of longitudinal FLAIR MRI volumes is proposed, based on non-linear gray value mapping, to quantify low-grade glioma growth. First, MRI volumes were mapped to a common range of gray levels via a midway-based histogram mapping. This mapping enabled direct comparison of MRI data and computation of difference maps. A statistical analysis framework of intensity distributions in midway-mapped MRI volumes as well as in their difference maps was designed to identify significant difference values, enabling quantification of low-grade glioma growth, around the borders of an initial segmentation. Two sets of parameters, corresponding to optimistic and pessimistic growth estimations, were proposed. The influence and modeling of MRI inhomogeneity field on a novel midway-mapping framework using image models with multiplicative contrast changes was studied. Clinical evaluation was performed on 32 longitudinal clinical cases from 13 patients. Several growth indices were measured and evaluated in terms of accuracy, compared to manual tracing. Results from the clinical evaluation showed that millimetric precision on a specific volumetric radius growth index measurement can be obtained automatically with the proposed differential analysis. The automated optimistic and pessimistic growth estimates behaved as expected, providing upper and lower bounds around the manual growth estimations. (C) 2011 Published by Elsevier B.V.
引用
收藏
页码:114 / 126
页数:13
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